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Customizable SnowPro Advanced: Data Engineer Certification Exam (DEA-C01) exam conditions in such a way that you can create your desired DEA-C01 exam with pre-determined questions and exam duration. You will be able to see instant results after going through the DEA-C01 practice exam. To confirm the product license, an active internet connection is required. An active 24/7 service has been provided for customers to resolve their issues. Use the SnowPro Advanced: Data Engineer Certification Exam (DEA-C01) practice test software to track your progress, as the software maintains track of all your efforts. The Snowflake DEA-C01 demo version is provided for customer satisfaction.

Snowflake DEA-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	SnowPro Advanced: Data Engineer Certification Exam
Exam Number:	DEA-C01
Related Certifications:	SnowPro Core Certification
Exam Duration:	115 minutes
Certificate Validity Period:	2 years
Exam Price:	$375 USD
Real Exam Qty:	Approximately 65 questions
Exam Format:	Scenario-based questions, Multiple select, Multiple choice
Passing Score:	Not publicly disclosed (Snowflake uses scaled scoring)
Available Languages:	English
Recommended Training:	SnowPro Advanced Data Engineer Exam Guide Snowflake University Training
Exam Registration:	Snowflake Certification Portal
Sample Questions:	Snowflake DEA-C01 Sample Questions
Exam Way:	Online proctored or authorized testing center
Pre Condition:	Recommended: SnowPro Core Certification or equivalent Snowflake experience
Official Syllabus URL:	https://www.snowflake.com/certifications/snowpro-advanced-data-engineer/

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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Data Transformation: The SnowPro Advanced: Data Engineer exam evaluates skills in using User-Defined Functions (UDFs), external functions, and stored procedures. It assesses the ability to handle semi-structured data and utilize Snowpark for transformations. This section ensures Snowflake engineers can effectively transform data within Snowflake environments, critical for data manipulation tasks.
Topic 2	Security: The Security topic of the DEA-C01 test covers the principles of Snowflake security, including the management of system roles and data governance. It measures the ability to secure data and ensure compliance with policies, crucial for maintaining secure data environments for Snowflake Data Engineers and Software Engineers.
Topic 3	Data Movement: Snowflake Data Engineers and Software Engineers are assessed on their proficiency to load, ingest, and troubleshoot data in Snowflake. It evaluates skills in building continuous data pipelines, configuring connectors, and designing data sharing solutions.
Topic 4	Performance Optimization: This topic assesses the ability to optimize and troubleshoot underperforming queries in Snowflake. Candidates must demonstrate knowledge in configuring optimal solutions, utilizing caching, and monitoring data pipelines. It focuses on ensuring engineers can enhance performance based on specific scenarios, crucial for Snowflake Data Engineers and Software Engineers.
Topic 5	Storage and Data Protection: The topic tests the implementation of data recovery features and the understanding of Snowflake's Time Travel and micro-partitions. Engineers are evaluated on their ability to create new environments through cloning and ensure data protection, highlighting essential skills for maintaining Snowflake data integrity and accessibility.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q349-Q354):

NEW QUESTION # 349
You are managing an Amazon S3 bucket used by your organization to store critical data files.
Recently, you've noticed that there have been accidental deletions and unintended modifications to important files. To address these issues, you need a strategy to ensure that you can recover previous versions of files and prevent data loss in the future.
Which S3 configuration is most suitable for protecting your data from accidental deletions and modifications while allowing you to recover previous versions of files?

A. Turn on versioning for the bucket to keep multiple versions of objects.
B. Configure Multi-Factor Authentication (MFA) Delete to add an extra layer of security for deleting objects.
C. Apply object lock with governance mode to prevent deletion or modification of objects.
D. Set expiration rules to automatically delete objects after a certain period.

Answer: A

Explanation:
Enabling S3 versioning allows you to preserve, retrieve, and restore every version of every object stored in your S3 bucket. This is the most effective method for protecting against accidental deletions and modifications because it maintains a history of changes, allowing you to recover previous versions of files.
References:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/Versioning.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-object.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuobject-lifecycle.html

NEW QUESTION # 350
A company stores data in Amazon S3 and Amazon RDS. The company needs to apply technical controls to meet security requirements. The company must generate backups of the data and retain the backups for specified retention periods. The company must protect the backups from accidental or malicious deletion during the retention periods.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create a backup plan in AWS Backup. Specify the backup schedule, set window and lifecycle values, and select a backup vault. Assign the Amazon S3 and Amazon RDS resources to the backup plan. Create a vault lock in compliance mode.
B. Create S3 buckets with versioning and Cross-Region Replication enabled. Set a backup retention period and backup window for each RDS DB instance. Use Amazon RDS automated backups.Take additional snapshots as required.
C. Create S3 buckets with versioning and MFA Delete enabled. Set a backup retention period and backup window for each RDS DB instance. Use the automated backup feature of Amazon RDS, and take additional snapshots as required.
D. Create S3 buckets with versioning and Same-Region Replication enabled. Set a backup retention period and backup window for each RDS DB instance. Use the automated backup feature of Amazon RDS. Take additional snapshots as required.

Answer: A

Explanation:
AWS Backup centrally automates backups for S3 and RDS with scheduled plans and lifecycle policies, and Vault Lock (compliance mode) enforces WORM immutability to prevent modification or deletion during retention, meeting security and retention requirements with minimal administration.

NEW QUESTION # 351
A data engineer needs a fully automated solution to check for new data in multiple databases and process data that the solution finds. The solution must run every hour. The solution must be compatible with Amazon RDS, Amazon DynamoDB, and Amazon OpenSearch Service. The solution must be able to process up to 10 MB of data at one time. The solution must be optimized for costs and operational overhead. The solution must have robust error handling capabilities.
Which solution will meet these requirements?

A. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to create a workflow that runs a directed acyclic graph (DAG) every hour to check for data. Configure the DAG to process identified data. Implement error handling in a Python operator.
B. Configure an Apache Spark application to run on Amazon EMR to check for data. Implement error handling in the application. Use Amazon EventBridge to invoke the application every hour.
C. Use Amazon EventBridge to invoke an AWS Lambda function every hour to check for data.
Configure the function to send a message to an Amazon Simple Queue Service (Amazon SQS) queue when the function finds new data. Use a second Lambda function to read the queue and perform the processing.
D. Use Amazon EventBridge to invoke AWS Step Functions every hour to deploy an AWS Lambda function to check for data. Configure Step Functions steps to process data that the Lambda function finds. Implement error handling in each state.

Answer: D

Explanation:
Amazon EventBridge can invoke AWS Step Functions on an hourly schedule, and Step Functions is a serverless orchestration service that is well suited for coordinating checks across multiple data sources while providing built-in retry and catch mechanisms for robust error handling. AWS Lambda can connect to Amazon RDS, Amazon DynamoDB, and Amazon OpenSearch Service through AWS SDKs, and Lambda can handle workloads well beyond 10 MB in memory, so this design meets the processing-size requirement with low cost and minimal operational overhead compared with EMR or MWAA.
Reference:
https://docs.aws.amazon.com/step-functions/latest/dg/tutorial-handling-error-conditions.html
https://docs.aws.amazon.com/opensearch-service/latest/developerguide/configuration- samples.html
https://docs.aws.amazon.com/lambda/latest/dg/configuration-memory.html
https://docs.aws.amazon.com/step-functions/latest/dg/workflow-studio-process-error.html

NEW QUESTION # 352
A data engineer set up an AWS Lambda function to read an object that is stored in an Amazon S3 bucket. The object is encrypted by an AWS KMS key.
The data engineer configured the Lambda function's execution role to access the S3 bucket.
However, the Lambda function encountered an error and failed to retrieve the content of the object.
What is the likely cause of the error?

A. The S3 bucket is located in a different AWS Region than the Region where the data engineer works. Latency issues caused the Lambda function to encounter an error.
B. The Lambda function's execution role does not have the necessary permissions to access the KMS key that can decrypt the S3 object.
C. The data engineer misconfigured the permissions of the S3 bucket. The Lambda function could not access the object.
D. The Lambda function is using an outdated SDK version, which caused the read failure.

Answer: B

NEW QUESTION # 353
Which are false statements about Star Schema?

A. The star schema is an important special case of the snowflake schema and is more effec-tive for handling simpler queries.
B. Star schema is more flexible in terms of analytical needs compared to Data Vault Mod-elling.
C. Star schemas are denormalized.
D. The star schema separates business process data into facts, which hold the measurable, quantitative data about a business, and dimensions which are descriptive attributes re-lated to fact data.

Answer: B

NEW QUESTION # 354
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